Sökning: "Drug information"

Visar resultat 1 - 5 av 333 uppsatser innehållade orden Drug information.

  1. 1. Erfarenheter av vården hos personer med substansbrukssyndrom : en litteraturöversikt

    Kandidat-uppsats, Sophiahemmet Högskola

    Författare :Ebba Bergqvist; Ella Jyrell; [2024]
    Nyckelord :Experience; Stigma; Substance related disorder; Stigma; Substansbrukssyndrom; Upplevelser;

    Sammanfattning : Bakgrund Substansbrukssyndrom är ett globalt hälsorelaterat problem. Det är en neuropsykiatrisk sjukdom som medför ett kraftigt behov av intag av droger trots skadliga konsekvenser. Behovet drivs av de belönade effekterna som drogerna har på hjärnan. LÄS MER

  3. 2. Quantification of Pharmaceuticals at the sub-cellular level using the NanoSIMS

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Analytisk kemi

    Författare :Maryam Dost; [2024]
    Nyckelord :Mass spectroscopy imaging; AstraZeneca; Nanosims; Therapeutics; pharmacokinetics; pharmacodynamics; Quantitative Visualization; calibration curve; RSF; pharmacology; Data Analysis; Chemistry; Quantification; isotopes; Pharmaceuticals; subcellular; drug; drug target; nucleotide; biodistribution; Bioanalytical electrochemistry; spectroscopy; mass spectrometry; analytical separations; Analytical Chemistry; ROI; Bioanalytical Chemistry; Masspektroskopi avbildning; AstraZeneca; Nanosims; Terapeutik; farmakokinetik; farmakodynamik; Kvantitativ visualisering; kalibreringskurva; RSF; farmakologi; Dataanalys; Kemi; Kvantifiering; isotoper; Läkemedel; subcellulär; läkemedel; läkemedelsmål; bioskopisk elektrofördelning; nukleotid; bioskopisk bioskopisk distribution; masspektrometri; analytiska separationer; analytisk kemi; bioanalytisk kemi;

    Sammanfattning : Mass spectroscopy imaging (MSI) has become a vital tool in modern research due to its ability to visualize the spatial distribution of molecules within tissue samples. The collaboration between researchers at AZ, the University of Gothenburg, and Chalmers University of Technology using the NanoSIMS instrument and MSI-SIMS technology has opened up new avenues of exploration in pharmaceutical development, particularly in examining drugs and metabolites at sub-cellular levels. LÄS MER

  4. 3. Delaktighet inom anestesiologisk omvårdnad : En begreppsanalys

    Magister-uppsats, Uppsala universitet/Anestesiologi och intensivvård

    Författare :Emilie Albertsson; Evelina Solem; [2023]
    Nyckelord :Participation; anesthesiological care; concept analysis; patient participation; Delaktighet; Anestesiologisk omvårdnad; begreppsanalys; patientdelaktighet;

    Sammanfattning : ABSTRACT Background: Participation is a concept that exists at different levels, in community organizations as well as health care. Being able to participate in one's care is a right by law in Sweden and a central part of person-centred care. Although participation is a well-established concept, there is no clear definition of the concept. LÄS MER

  5. 4. Combining Cell Painting, Gene Expression and Structure-Activity Data for Mechanism of Action Prediction

    Master-uppsats, Uppsala universitet/Nationellt resurscentrum för biologi och bioteknik

    Författare :Erik Everett Palm; [2023]
    Nyckelord :bioinformatics; deep learning; machine learning; joint model; tabular data; image data;

    Sammanfattning : The rapid progress in high-throughput omics methods and high-resolution morphological profiling, coupled with the significant advances in machine learning (ML) and deep learning (DL), has opened new avenues for tackling the notoriously difficult problem of predicting the Mechanism of Action (MoA) for a drug of clinical interest. Understanding a drug's MoA can enrich our knowledge of its biological activity, shed light on potential side effects, and serve as a predictor of clinical success. LÄS MER

  7. 5. Analyzing the performance of active learning strategies on machine learning problems

    Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Avdelningen för systemteknik

    Författare :Vendela Werner; [2023]
    Nyckelord :computer science; bioinformatics; machine learning; active learning; artificial intelligence; supervised learning; Astrazeneca; maskininlärning; artificiell intelligens; datorvetenskap; active learning; bioinformatik; supervised learning;

    Sammanfattning : Digitalisation within industries is rapidly advancing and data possibilities are growing daily. Machine learning models need a large amount of data that are well-annotated for good performance. To get well-annotated data, an expert is needed, which is expensive, and the annotation itself could be very time-consuming. LÄS MER